(geo)graphs - Complex Networks as a shapefile of nodes and a shapefile of edges for different applications

نویسندگان

  • Leonardo B. L. Santos
  • Aurelienne A. S. Jorge
  • Marcio Rossato
  • Jessica D. Santos
  • Onofre A. Candido
  • Wilson Seron
  • Charles N. de Santana
چکیده

Spatial dependency and spatial embedding are basic physical properties of many phenomena modeled by networks. The most indicated computational environment to deal with spatial information is to use Georeferenced Information System (GIS) and Geographical Database Management Systems (GDBMS). Several models have been proposed in this direction, however there is a gap in the literature in generic frameworks for working with Complex Networks in GIS/GDBMS environments. Here we introduce the concept of (geo)graphs: graphs in which the nodes have a known geographical location and the edges have spatial dependence. We present case studies and two open source softwares (GIS4GRAPH and GeoCNet) that indicate how to retrieve networks from GIS data and how to represent networks over GIS data by using (geo)graphs.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Toughness of the Networks with Maximum Connectivity

The stability of a communication network composed of processing nodes and communication links is of prime importance to network designers. As the network begins losing links or nodes, eventually there is a loss in its effectiveness. Thus, communication networks must be constructed to be as stable as possible, not only with respect to the initial disruption, but also with respect to the possible...

متن کامل

نقشه‌سازی مناطق شبه ایندومالاین و آفروتروپیکال ایران در وضوح شهرستان

Background and Objectives: Iran is classically located in the Palearctic zoogeographic zone, but southern pasts of Iran are drastically different from other parts in terms of fauna and flora. Nowadays, considering the technological advances and the ability to locate the zone border using aerial photos, and the need for comparing the prevalence of the diseases in different locations, it is neces...

متن کامل

finding influential individual in Social Network graphs using CSCS algorithm and shapley value in game theory

In recent years, the social networks analysis gains great deal of attention. Social networks have various applications in different areas namely predicting disease epidemic, search engines and viral advertisements. A key property of social networks is that interpersonal relationships can influence the decisions that they make. Finding the most influential nodes is important in social networks b...

متن کامل

A Fast Approach to the Detection of All-Purpose Hubs in Complex Networks with Chemical Applications

A novel algorithm for the fast detection of hubs in chemical networks is presented. The algorithm identifies a set of nodes in the network as most significant, aimed to be the most effective points of distribution for fast, widespread coverage throughout the system. We show that our hubs have in general greater closeness centrality and betweenness centrality than vertices with maximal degree, w...

متن کامل

Estimation of Network Reliability for a Fully Connected Network with Unreliable Nodes and Unreliable Edges using Neuro Optimization

In this paper it is tried to estimate the reliability of a fully connected network of some unreliable nodes and unreliable connections (edges) between them. The proliferation of electronic messaging has been witnessed during the last few years. The acute problem of node failure and connection failure is frequently encountered in communication through various types of networks. We know that a ne...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1711.05879  شماره 

صفحات  -

تاریخ انتشار 2017